• Title/Summary/Keyword: Image output system

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Rotation and scale-invariant pattern recognition using WCHF-fSDF filter (WCHF-fSDF 필터를 이용한 회전과 크기불변 패턴 인식)

  • 이승희;김철수;이하운;도양회;박세준;김수중
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.2
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    • pp.392-400
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    • 1997
  • In this paper we porposed WCHF-fSDF filter to obtain a roration and scale-invariant correlation output. WCHF-fSDF filter is synthesized by each single CHF exttracted from scale-changed and wavelet tranformed imagesfor a refereence image as tranining images. The wavelet transform is defined as the correlation of an input image with a wavelet function. Therefore two 4f optical correlation systems are needed for pattern recognition using wavelet transform. We here include the wavelet function for the input image in the process of the proposed filter design and substitute the two 4f optical correlation system with a single 4f optical correlation system. The Performances of the proposed filter are compared with conventional CHF-SDF, POCHF-SDF filters through the computer simulation. The results of computer simulation show that the proposed filter has the rotation and scale-invariant correlation output and it has better performances than thoseof the conventioanl filters.

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Prewarping Techniques Using Fuzzy system and Particle Swarm Optimization (퍼지 시스템과 Particle Swarm Optimization(PSO)을 이용한 Prewarping 기술)

  • Jang, Woo-Seok;Kang, Hwan-Il;Lee, Byung-Hee
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.10c
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    • pp.367-370
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    • 2007
  • In this paper, we concentrate on the mask design problem for optical micro-lithography. The pre-distorted mask is obtained by minimizing the error between the designed output image and the projected output image. We use the particle swarm optimization(PSO) and fuzzy system to insure that the resulting images are identical to the desired image. Our method has good performance for the iteration number by an experiment.

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A Study on the Construction of a Document Input/Output system (문서 입출력 시스템의 구성에 관한 연구)

  • 함영국;도상윤;정홍규;김우성;박래홍;이창범;김상중
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.10
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    • pp.100-112
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    • 1992
  • In this paper, an integrated document input/output system is developed which constructs the graphic document from a text file, converts the document into encoded facsimile data, and also recognizes printed/handwritten alphanumerics and Korean characters in a facsimile or graphic document. For an output system, we develop the method which generates bit-map patterns from the document consisting of the KSC5601 and ASCII codes. The binary graphic image, if necessary, is encoded by the G3 coding scheme for facsimile transmission. For a user friendly input system for documents consisting of alphanumerics and Korean characters obtained from a facsimile or scanner, we propose a document recognition algirithm utilizing several special features(partial projection, cross point, and distance features) and the membership function of the fuzzy set theory. In summary, we develop an integrated document input/output system and its performance is demonstrated via computer simulation.

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Analysis and synthesis of facial expressions in knowledge-based image coding (지적화상부호화에 있어서 표정분석과 합성)

  • ;Harashima, Hiroshi;Takebe, Tsyosi
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.451-456
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    • 1989
  • New image coding system for facial images called 'Knowledge-based image coding' is described, in which input image is analyzed and output image is synthesized using analysis results. Analysis and synthesis method of facial expressions are presented. Synthesis rules are determined on the basis of facial muscles and are also used in analysis process to produce a faithful reconstruction of the original image. A number of examples are shown.

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Motion Tracking Algorithm for A CCTV System (CCTV 시스템을 위한 움직임 추적 기법)

  • Kang, Seoung-Il;Hong, Sung-Hoon
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.295-296
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    • 2006
  • This paper implements a method that tracking the moving objects that detected by the motion detection function of the digital CCTV system. We simply implement the motion detection function of the digital CCTV system that use frame difference and thresholding. When motion is detected, the motion detection function generates two outputs. One output is the event that the motion is arised in input image frame. The other output is coordinate that motion is exists. Then, do the block matching algorithm[2] using coordinate, that motion is exists, as initial coordinate of the block matching algorithm. The best matched coordinate is new initial coordinate of the block matching algorithm for the next image frame. We simply use the block matching algorithm that implements tracking the moving objects. It is simple, but useful the actual digital CCTV system.

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A study on correspondence problem of stereo vision system using self-organized neural network

  • Cho, Y.B.;Gweon, D.G.
    • Journal of the Korean Society for Precision Engineering
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    • v.10 no.4
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    • pp.170-179
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    • 1993
  • In this study, self-organized neural network is used to solve the vorrespondence problem of the axial stereo image. Edge points are extracted from a pair of stereo images and then the edge points of rear image are assined to the output nodes of neural network. In the matching process, the two input nodes of neural networks are supplied with the coordi- nates of the edge point selected randomly from the front image. This input data activate optimal output node and its neighbor nodes whose coordinates are thought to be correspondence point for the present input data, and then their weights are allowed to updated. After several iterations of updating, the weights whose coordinates represent rear edge point are converged to the coordinates of the correspondence points in the front image. Because of the feature map properties of self-organized neural network, noise-free and smoothed depth data can be achieved.

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Invariant Range Image Multi-Pose Face Recognition Using Fuzzy c-Means

  • Phokharatkul, Pisit;Pansang, Seri
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1244-1248
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    • 2005
  • In this paper, we propose fuzzy c-means (FCM) to solve recognition errors in invariant range image, multi-pose face recognition. Scale, center and pose error problems were solved using geometric transformation. Range image face data was digitized into range image data by using the laser range finder that does not depend on the ambient light source. Then, the digitized range image face data is used as a model to generate multi-pose data. Each pose data size was reduced by linear reduction into the database. The reduced range image face data was transformed to the gradient face model for facial feature image extraction and also for matching using the fuzzy membership adjusted by fuzzy c-means. The proposed method was tested using facial range images from 40 people with normal facial expressions. The output of the detection and recognition system has to be accurate to about 93 percent. Simultaneously, the system must be robust enough to overcome typical image-acquisition problems such as noise, vertical rotated face and range resolution.

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Design of Unsharp Mask Filter based on Retinex Theory for Image Enhancement

  • Kim, Ju-young;Kim, Jin-heon
    • Journal of Multimedia Information System
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    • v.4 no.2
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    • pp.65-73
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    • 2017
  • This paper proposes a method to improve the image quality by designing Unsharp Mask Filter (UMF) based on Retinex theory which controls the frequency pass characteristics adaptively. Conventional unsharp masking technique uses blurring image to emphasize sharpness of image. Unsharp Masking(UM) adjusts the original image and sigma to obtain a high frequency component to be emphasized by the difference between the blurred image and the high frequency component to the original image, thereby improving the contrast ratio of the image. In this paper, we design a Unsharp Mask Filter(UMF) that can process the contrast ratio improvement method of Unsharp Masking(UM) technique with one filtering. We adaptively process the contrast ratio improvement using Unsharp Mask Filter(UMF). We propose a method based on Retinex theory for adaptive processing. For adaptive filtering, we control the weights of Unsharp Mask Filter(UMF) based on the human visual system and output more effective results.

ANALYSIS ON RECEIVING PERFORMANCE FOR KOMPSAT-5 X-BAND IMAGE DATA

  • Park, Durk-Jong;Kang, Chi-Ho;Ahn, Sang-II
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.208-211
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    • 2008
  • Band-limited filtering will be applied to remove interference resulted from two neighbored channels in the transmission of KOMPSAT-5 X-Band image data. In that case, receiver in ground station should prepare righteous matched filter to avoid huge BER degradation depending on the matched filter of COTS receiver. As an effort to simulate the bandlimited filtering, test filter was designed and manufactured on the basis of main specification for output filter of KOMPSAT-5 satellite. Consequently, 1.8dB of BER degradation was measured at the output of test band-pass filter, but the degradation was downsized up to 0.4dB thanks to the adaptive matched filter of COTS receiver.

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Adaptive Classification of Subimages by the Fuzzy System for Image Data Compression (퍼지시스템에 의한 부영상의 적응분류와 영상데이타 압축에의 적용)

  • Kong, Seong-Gon
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.43 no.7
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    • pp.1193-1205
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    • 1994
  • This paper presents a fuzzy system that adaptively classifies subimages to four classes according to image activity distribution. In adaptive transform image coding, subimage classification improves the compression performance by assigning different bit maps to different classes. A conventional classification method sorts subimages by their AC energy and divides them to classes with equal number of subimages. The fuzzy system provides more flexible classification to natural images with various distribution of image details than does the conventional method. Clustering of training data in the input-output product space generated the fuzzy rules for subimage classification. The fuzzy system of small number of fuzzy rules successfully classified subimages to improve the compression performance of the transform image coding without sorting of AC energies.